A Framework to Accelerate Protein Structure Comparison Tools

Abstract

At the center of computational structural biology, protein structure comparison is a key problem. The steady increase in the number of protein structures encourages the development of massively parallel tools. While the focus of research is to propose data-analytical methods to tackle this problem, there are limited research proposing generic tools to run these methods in parallel environments. Herein, we propose a scalable framework to handle this steady increase. The proposed framework runs the sequential tools on parallel environments. It is a GUI-based and requiring no scripting or installation procedures. The framework includes optimally distributing protein structure database over the existing computing resources, tracking the remote processes course of execution, and merging the results to form the final output. The first stage realizes the biological database distribution as an optimization problem in order to maximize the cluster resources utilization and minimize the execution time. The experimental results show linear and nearly optimal speedups with no loss in accuracy. The framework is available at http://biocloud.hnu.edu.cn/ppsc/.